Figure 2: The clustering effect that results from imposing a stick-breaking prior on the gene and class- specific model parameters, θil. A matrix of indicator variables is used to cluster the observed count data into a finite number of groups, where the genes in each group share the same model parameters. The number of clusters is not known a priori. The distribution of weight mass among the various clusters in the model is determined by parameter η.